Surface-Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues.

Surface-enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate preparation that enhances Raman signal strength on a global scale. To systematically solve these problems, artificial intelligence techniques are applied to analyze the signals of pesticides based on 3D and dynamic SERS imaging. Utilizing perovskite/silver nanoparticles composites (CaTiO3/Ag@BONPs) as enhanced substrates, enabling it not only to cleanse pesticide residues from the surface to pulp of fruits and vegetables, but also to investigate the penetration dynamics of an array of pesticides (chlorpyrifos, thiabendazole, thiram, and acetamiprid). The findings challenge existing paradigms, unveiling a previously unnoticed weakening process during pesticide invasion and revealing the surprising permeability of non-systemic pesticides. Of particular note is easy to overlook that the combined application of pesticides can inadvertently intensify their invasive capacity due to pesticide interactions. The innovative study delves into the realm of pesticide penetration, propelling a paradigm shift in the understanding of food safety. Meanwhile, this strategy provides strong support for the cutting-edge application of SERS imaging technology and also brings valuable reference and enlightenment for researchers in related fields.

Integrated surface-enhanced Raman spectroscopy and convolutional neural network for quantitative and qualitative analysis of pesticide residues on pericarp.

Pesticide residue poses a significant global public health concern, necessitating improved detection methods. Here, a novel platform was introduced based on surface-enhanced Raman spectroscopy (SERS) to detect ten distinct types of pesticides. Notably, the sensitivity of this approach is exemplified by detecting trace amounts of 50 pM (10 ppt) thiabendazole. The correlation between the characteristic peak intensity of coexisting pesticides and their concentrations displays an exceptional linear relationship (R2 = 0.9999), underscoring its utility for quantitative mixed pesticide detection. Additionally, qualitative analysis of five mixed pesticides was conducted leveraging distinctive peak labeling. Harnessing machine learning techniques, a model for classifying and predicting pesticides on pericarps was developed. Remarkably, the convolutional neural network achieved classification accuracy of 100 % and prediction accuracy of 99.62 %. This innovative approach accurately identifies and quantifies diverse pesticides, thus offering a feasible scheme for in-situ detection of pesticide residues. Ultimately, this strategy contributes to ensuring food safety and public health.

[Preparation and application of melamine molecularly imprinted photonic crystal hydrogel sensor].

In this paper, molecularly imprinted photonic crystal hydrogels (MIPHs) were prepared by combining photonic crystals with molecular imprinting technology. The MIPHs were used as optical sensors for the rapid reorganization and detection of melamine in water samples. In this experiment, melamine was used as a template molecule, and the MIPHs were prepared by successive self-assembly, polymerization, and template removal. Morphological characterization by scanning electron microscopy (SEM) showed that the MIPHs possessed a highly ordered three-dimensional (3D) macroporous structure containing nanocavities. As optical sensors, the MIPHs were able to transform molecular recognition events into fluorescence signals for rapid and highly selective and sensitive recognition of the target molecule. Based on color changes of the MIPHs, the target analyte could be quickly identified by analysis with image software or even by observation with the naked eye. Under optimal conditions, the Bragg diffraction peak of the MIPHs shifted from 563 to 608 nm when exposed to melamine in mass concentrations of 10-11 to 10-6mol/L, whereas there were no obvious peak shifts when it was exposed to structural analogues of melamine.